Krzysztof Podgórski


Personal profile


My research belongs to the area of broadly understood applied probability.
While I consider myself well-trained both in the probability theory and the theory of statistics, I have also extensive experience in modern computationally intense methods of statistics.
Throughout my career I took on a very wide spectrum of problems with both theoretical and applied flavor.
My contributions are in ergodic theory of stochastic processes, bootstrap methods for regression analysis, theory of heavy tailed distributions, non-Gaussian random fields, extreme value theory but also on occasions I have contributed to fields that are more distant to my main interests such as non-commutative probability, information theory, and methodology of science.
I have also a considerable number of publications in areas other than statistics and probability such as ocean and mechanical engineering, environmental, actuarial and medical sciences, where I have presented the developed models in a concrete empirical context.
I enjoy collaborative and interdisciplinary efforts and have a wide spectrum of collaborators both in the theoretical and applied fields.
My current research interests can be grouped into the following three general categories
1. theory and applications of multivariate non-Gaussian stochastic models,
2. statistical analysis of spatial random fields evolving in time with non-trivial dynamics,
3. statistical distributions at random crossing events.

While the focus each of the three areas is clearly distinct, typically and naturally in many of my work there is a strong overlap between two or even all three of them.
I am greatly interested in applications of the developed methodologies and thus proposed them in multidisciplinary research in: mechanical engineering (modeling road profiles and responses to them), ocean engineering (wave models, ship routes, storms), spatial econometrics (multivariate models for linkages between markets), actuarial sciences (non-Gaussian claim models), mathematical finance (detecting common jumps in high-frequency multivariate financial data).

Interests: Stochastic Processes, Random Spatio-temporal Fields, Non-Gaussian Stochastic Models, Applications to Engineering, Mathematical Finance, Environmental Sciences, Modelling of Sea Surfaces, Computationally Intensive Methods of Statistics


Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 14 - Life Below Water

UKÄ subject classification

  • Probability Theory and Statistics

Free keywords

  • stochastic modelling
  • statistical inference
  • theory of probability distributions


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Collaborations the last five years

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